The NASA Carbon Monitoring System

Abstract:

Greenhouse gas emission inventories, forest carbon sequestration programs (e.g., Reducing Emissions from Deforestation and Forest Degradation (REDD and REDD+), cap-and-trade systems, self-reporting programs, and their associated monitoring, reporting and verification (MRV) frameworks depend upon data that are accurate, systematic, practical, and transparent. A sustained, observationally-driven carbon monitoring system using remote sensing data has the potential to significantly improve the relevant carbon cycle information base for the U.S. and world. Initiated in 2010, NASA’s Carbon Monitoring System (CMS) project is prototyping and conducting pilot studies to evaluate technological approaches and methodologies to meet carbon monitoring and reporting requirements for multiple users and over multiple scales of interest. NASA’s approach emphasizes exploitation of the satellite remote sensing resources, computational capabilities, scientific knowledge, airborne science capabilities, and end-to-end system expertise that are major strengths of the NASA Earth Science program. Through user engagement activities, the NASA CMS project is taking specific actions to be responsive to the needs of stakeholders working to improve carbon MRV frameworks. The first phase of NASA CMS projects focused on developing products for U.S. biomass/carbon stocks and global carbon fluxes, and on scoping studies to identify stakeholders and explore other potential carbon products. The second phase built upon these initial efforts, with a large expansion in prototyping activities across a diversity of systems, scales, and regions, including research focused on prototype MRV systems and utilization of COTS technologies. Priorities for the future include: 1) utilizing future satellite sensors, 2) prototyping with commercial off-the-shelf technology, 3) expanding the range of prototyping activities, 4) rigorous evaluation, uncertainty quantification, and error characterization, 5) stakeholder engagement, 6) partnerships with other U.S. agencies and international partners, and 7) modeling and data assimilation.